ON SOME CLASSES OF THE WEAKLY SUBDIFFERENTIAL FUNCTIONS
Yıl 2025,
Cilt: 13 Sayı: 1, 24 - 34, 28.02.2025
Samet Bila
,
Refail Kasımbeyli
Öz
This work presents a theorem that any Lipschitz function is weakly subdifferentiable with x^* component of the weak subgradient is different from 0_(R^n ). This theorem is based on Kasimbeyli's nonlinear cone separation theorem. Also, we show that any positively homogeneous and continuous function is both upper and lower Lipschitz. Additionally, we show that positively homogeneous and lower semicontinuous functions are weakly subdifferentiable that the pair (x^*,c) which is a weak subgradient of a function in this case is different from (0_(R^n ),0).
Kaynakça
- [1] Azimov AY, Gasimov RN. On weak conjugacy, weak subdifferentials and duality with zero gap in nonconvex optimization, International Journal of Applied Mathematics, 1, 1999, pp. 171–192.
- [2] Azimov AY, Gasimov RN. Stability and duality of nonconvex problemsvia augmented lagrangian, Cybernatics and System Analysis, 3(3), 2002, pp. 412–421.
- [3] Bila S, Kasimbeyli R. On the some sum rule for the weak subdifferential and some properties of augmented normal cones, Journal of Nonlinear and Convex Analysis, 24(10), 2023, pp. 2239–2257.
- [4] Borwein JM, Lewis AS. Convex Analysis and Nonlinear Optimization, CMS Books in Mathematics, Springer Science+Business Media, Inc., New York, 2006.
- [5] Dinc Yalcin G, Kasimbeyli R. Weak subgradient method for solving non-smooth nonconvex optimization problems, Optimization, 70(7), 2021, pp. 1513-1553.
- [6] Gasimov RN. Duality in nonconvex optimization, Ph.D. Dissertation, Department of Operations Research and Mathematical Modeling, Baku State University, Baku, 1992.
- [7] Gasimov RN. Augmented Lagrangian duality and nondifferentiable optimization methods in nonconvex programming, J. Global Optimization, 24, 2002, pp. 187–203.
- [8] Kasimbeyli R, Mammadov M. Optimality conditions in nonconvex opti-mization via weak subdifferentials, Nonlinear Analysis: Theory, Methods and Applications, 74, 2011, pp. 2534–2547.
- [9] Kasimbeyli R, Mammadov M. On weak subdifferentials, directional derivatives, and radial epiderivatives for nonconvex functions, SIAM J. on Optimization, 20, 2009, pp. 841–855
- [10] Kasimbeyli R. A nonlinear cone separation theorem and scalarization in nonconvex vector optimization, SIAM J. on Optimization, 20, 2010, pp. 1591–1619.
- [11] Kasimbeyli R, Karimi M. Separation theorems for nonconvex sets and application in optimization, Operations Research Letters, 47, 2019, pp. 569–573.
- [12] Rockafellar RT. Convex analysis, Princeton University Press, Princeton, 1970.
- [13] Rockafellar RT, Wets R. J-B. Variational analysis, Springer-Verlag Berlin Heidelberg, 2009.
ON SOME CLASSES OF WEAKLY SUBDIFFERENTIABLE FUNCTIONS
Yıl 2025,
Cilt: 13 Sayı: 1, 24 - 34, 28.02.2025
Samet Bila
,
Refail Kasımbeyli
Öz
This work presents a theorem that any Lipschitz function is weakly subdifferentiable with x^* component of the weak subgradient is different from 0_(R^n ). This theorem is based on Kasimbeyli's nonlinear cone separation theorem. Also, we show that any positively homogeneous and continuous function is both upper and lower Lipschitz. Additionally, we show that positively homogeneous and lower semicontinuous functions are weakly subdifferentiable that the pair (x^*,c) which is a weak subgradient of a function in this case is different from (0_(R^n ),0).
Kaynakça
- [1] Azimov AY, Gasimov RN. On weak conjugacy, weak subdifferentials and duality with zero gap in nonconvex optimization, International Journal of Applied Mathematics, 1, 1999, pp. 171–192.
- [2] Azimov AY, Gasimov RN. Stability and duality of nonconvex problemsvia augmented lagrangian, Cybernatics and System Analysis, 3(3), 2002, pp. 412–421.
- [3] Bila S, Kasimbeyli R. On the some sum rule for the weak subdifferential and some properties of augmented normal cones, Journal of Nonlinear and Convex Analysis, 24(10), 2023, pp. 2239–2257.
- [4] Borwein JM, Lewis AS. Convex Analysis and Nonlinear Optimization, CMS Books in Mathematics, Springer Science+Business Media, Inc., New York, 2006.
- [5] Dinc Yalcin G, Kasimbeyli R. Weak subgradient method for solving non-smooth nonconvex optimization problems, Optimization, 70(7), 2021, pp. 1513-1553.
- [6] Gasimov RN. Duality in nonconvex optimization, Ph.D. Dissertation, Department of Operations Research and Mathematical Modeling, Baku State University, Baku, 1992.
- [7] Gasimov RN. Augmented Lagrangian duality and nondifferentiable optimization methods in nonconvex programming, J. Global Optimization, 24, 2002, pp. 187–203.
- [8] Kasimbeyli R, Mammadov M. Optimality conditions in nonconvex opti-mization via weak subdifferentials, Nonlinear Analysis: Theory, Methods and Applications, 74, 2011, pp. 2534–2547.
- [9] Kasimbeyli R, Mammadov M. On weak subdifferentials, directional derivatives, and radial epiderivatives for nonconvex functions, SIAM J. on Optimization, 20, 2009, pp. 841–855
- [10] Kasimbeyli R. A nonlinear cone separation theorem and scalarization in nonconvex vector optimization, SIAM J. on Optimization, 20, 2010, pp. 1591–1619.
- [11] Kasimbeyli R, Karimi M. Separation theorems for nonconvex sets and application in optimization, Operations Research Letters, 47, 2019, pp. 569–573.
- [12] Rockafellar RT. Convex analysis, Princeton University Press, Princeton, 1970.
- [13] Rockafellar RT, Wets R. J-B. Variational analysis, Springer-Verlag Berlin Heidelberg, 2009.